WHAT ARE TMY & AMY FILES? WHITE PAPER. A Summary of Weather Files and Climate Data Input for Modeling

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Mervin Patterson
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1 WHAT ARE TMY & AMY FILES? WHITE PAPER A Summary of Weather Files and Climate Data Input for Modeling

2 HISTORY AND TYPES OF CLIMATE DATA History and Types of Climate Data Modern building codes were not enacted until about 1905 in the U.S., and these relied on climate zones created by dividing the country into less than a dozen areas based on generalized weather conditions. Although improved somewhat, these zones have not substantially changed in the past 100 years and are still very much in use today. While useful in the gross sizing of HVAC capacities, these zones lack the precision required for any type of energy modeling or analysis. TMY FILES TMY (Typical Meteorological Year) files were first created by the U.S. Department of Energy s (DOE) National Renewable Energy Laboratory (NREL) in 1981 [an advancement of the TRY (Test Reference Year) Files created in 1976 by the National Climatic Data Center] as a more localized and comprehensive indicator of the climate to further assist in the capacity planning of HVAC systems. TMY files are created by looking at years of hourly data at the site in question (usually a weather station) and selecting, in series, the most typical January, February, and so on of all available years based on a weighted average of eleven weather variables with the selected months knitted together into one synthetic year of typical months. The initial TMY file was subsequently replaced by two primary types of TMY files TMY2 files that use 30 years of data replaced the initial TMY file in about 1990, with an enhanced weighted average selection method. Approximately 1,000 TMY2 files were created from weather station data from mostly from airport-based stations. These served as the default EnergyPlus weather files until late in TMY3 files that use 15 years of data were introduced in 2005 with a higher emphasis on solar radiation variables and also included precipitation as a variable. While statistically stable files require 30 years of data, the TMY3 utilized only 15 because that is the period where adequate satellite input was available effectively increasing the availability and accuracy of the solar radiation data. In late 2010, the DOE EnergyPlus converted to this file type as the default. TMY3 files are available for about 2,500 sites primarily in the United States and Europe. Other condensed weather data sets used for the same purpose include IWEC2 (developed by ASHRAE), CWEC (developed by the WASUN simulation laboratory), and CTZ2 [developed by the California Energy Commission (CEC)]. CAUTIONS WITH TMY FILES 1. They miss the extremes. They do a good job capturing typical conditions but (by design) do not show the extremes. This becomes increasingly important as the movement toward energy efficient design drives heating and cooling systems to be only as big as they have to be Page 1 Weather Analytics

3 HISTORY AND TYPES OF CLIMATE DATA introducing a vulnerability to being overtaxed with extreme conditions they were not designed to handle. 2. They are not likely to be local. Unless your site is near an airport, they do not necessarily represent the climate at your site. They are created from where the measurements were which generally means airports and the applicability of the climate in a file reduces with both distance and terrain change away from that station. 3. They provide sparse international coverage. Because there are only a few thousand weather stations that have been operating with greater than 50% completeness over the last years, there are only a few thousand TMY files available and those tend to be concentrated in North America and Europe. 4. They are not all current and built with all the years. Not all TMY files are constructed with years of data and some may have been constructed as much as 20 years ago, therefore representing the typical climate for the years prior to that date. Since the results of models and simulations are only as accurate as the assumptions of the heating and cooling loads placed on the building, the actual content and limitations of the TMY files need to be well understood, particularly with the move to energy efficient design. AMY FILES TMY files cannot be used to monitor, manage or confirm the actual performance of a building. This requires AMY (Actual Meteorological Year) files, which are actual hourly data sets over the last year or time period where energy use data is available, but put into the same formats as a TMY file. AMY files can also be used as input alternatives to TMY files if selected for years with more extreme weather to cross-check designs under stress. Since daily or hourly comparisons require more precision than general design demands, AMY files need to be as close to the building as possible. SOME CAUTIONS WITH AMY FILES 1. Location is essential. AMY files may have been created from a local airport station. The applicability of the weather conditions in a file reduces with both distance and terrain change away from that station, so it is best to get actual data as close as possible to the building site. 2. Modeling systems have a variety of expectations. Care must be taken to match the AMY file with the requirements of the modeling tool being used in both format and duration. Some will not take partial years and each has their own way of handling files that cross year boundaries. Some require all files to start with the month of January; others do not. Ongoing monitoring and performance optimizing will require continued access to on- or near-site actual weather conditions and this may extend to precision forecasted conditions to drive predictive control. It is good if this is as local to the building as possible and from the same site or at least calibrated to the Page 2 Weather Analytics

4 HISTORY AND TYPES OF CLIMATE DATA source of the AMY file(s) used in the modeling. Note that energy consumption is not just driven by external air temperature. Humidity, wind speed and direction, direct and indirect solar radiation, and reflected heat from the ground and surroundings need to be considered as well. SOURCE DATA FOR TMY AND AMY WEATHER FILES There are two primary sources for climate data: Direct Observations: Weather Stations (ground, buoys, balloons) Generally accurate but measure a limited number of variables (5 10) Only ~3,000 worldwide operating for 30+ years and only 1,000 of them with >80% completeness Only ~4,000 today operate with >80% completeness Only a few hundred measure solar radiation satellites. Those that do require significant post processing to integrate cloud image data with top of atmosphere radiation. Only widely available and in sufficient quality for the last 15 years Modeled data: Reanalysis data Gap free data uniformly distributed across region or globe with all variables Area based, gridded data representing the average over the grid Regional (North America) files can have grid resolution of 1 5 km. Global datasets are 35 km. Mesoscale model data Full or partial atmospheric models run for individual sites A TMY or AMY file can be created from either of these sources independently or in combination. Nearly all publicly available TMY files are from weather station sites (mostly airports) with the solar radiation variables added from tables of post-processed satellite observations for that site. Some modeling programs have their own internal TMY files generated using a mesoscale modeling technique. It is possible to create TMY and AMY files localized to sites away from weather stations by integrating the weather station observations with gridded reanalysis data. Page 3 Weather Analytics

5 ABOUT WEATHER ANALYTICS About Weather Analytics Weather Analytics delivers global climate intelligence by providing statistically stable, gap-free data formed by an extensive collection of historical, current and forecasted weather content, coupled with proprietary analytics and methodologies. Weather Analytics finds, assembles, cleans and formats weather data from around the world and delivers information that is directly accessible in an online database for decision support. Weather Analytics uses the aggregated data to create with proprietary analytics more than 580 weather variables for enhanced weather intelligence and risk mitigation that is delivered in userfriendly formats allowing customers to focus efforts on solving business problems versus aggregating and cleansing data from raw sources. Weather Analytics provides this weather information for each of more than 700,000 locations, which covers the entire globe. The comprehensive collection ranges from 33 years of historical climate data, to on-demand current conditions, to hourly seven-day forecasts, all available for purchase at. Contact Information Weather Analytics 8403 Colesville Road, Suite 1100 Silver Spring, MD Page 4 Weather Analytics

CASE STUDY: COOLERADO CORPORATION

CASE STUDY: COOLERADO CORPORATION Coolerado uses Weather Analytics climate data to demonstrate to clients the energy-efficiency of their air conditioners in places around the globe. 02 Overview Coolerado